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Fundamentals of statistics

General data

Course ID:	1300-OPST2CW
Erasmus code / ISCED:	11.201 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0542) Statistics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Fundamentals of statistics
Name in Polish:	Podstawy statystyki
Organizational unit:	Faculty of Geology
Course groups:	(in Polish) Przedmioty obowiazkowe na II roku studiów pierwszego stopnia na kierunku geologia poszukiwawcza (in Polish) Przedmioty obowiązkowe na II r. studiów I st. na kierunku geologia stosowana na specjalizacji GKG (in Polish) Przedmioty obowiązkowe na II r. studiów I st. na kierunku geologia stosowana na specjalizacji GS (in Polish) Przedmioty obowiązkowe na II r. studiów I st. na kierunku geologia stosowana na specjalizacji ISM
ECTS credit allocation (and other scores):	3.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language:	Polish
Type of course:	obligatory courses
Prerequisites (description):	Student should have a basic knowledge connected with: • differential calculus for one-variable function, • integral calculus, definite Riemann integral, improper integral.
Short description:	Definition of probability and its properties. Random variables, parameters of distribution. Distributions of random variables: binomial, Poisson, chi-square, Student`s distributions, n–dimension random variables. Basic statistics notions, methods of sample collections. One-dimensional statistical series and their elaboration: distributive series, diagram, histogram, distribution parameters. Range estimation, confidence intervals for average value and variance. Verification of statistical hypothesizes, tests of significances. Two-dimensional population, regression line, coefficient of linear correlation (least squares method), curvilinear correlation.
Full description:	The lecture has the task to know with the following subject matters: • elements of probability definitions: classical, geometrical, axiomaltical, statistical, • random variables discrete and continuous and their parameters. Distributions of random variables: binomial, Poisson, normal, chi-square, Student`s distributions, • n-dimensional random variables, • basic statistics notions, methods of sample collections, • one dimensional statistical series and their elaboration, distributive series, diagram, histogram, distribution parameters, • point estimation, confidence intervals for average value and variance, • verification of statistical hypothesises, tests of significances, • two-dimensional populations, regression lines, coefficient of linear correlations (least squares method), curvilinear correlation. The exercises will be devoted for solving of the problems based on the theory presented on lectures, • are synchronized with lectures, • teach to solve of exercises, calculations, • teach to solve some examples illustrative the lecture theory, • teach to interpret of the obtained results, • indicate numerical programs for the statistical problems.
Bibliography:	(in Polish) PLATT, C. 1977. Problemy rachunku prawdopodobieństwa i statystyki matematycznej. Wydawnictwo Naukowe PWN; Warszawa KRYSICKI W., BARTOS J., DYCZKA W., KROLIKOWSKA K., WASILEWSKA M., 1998, Rachunek prawdopodobieństwa i statystyka matematyczna, Wydawnictwo Naukowe PWN, Warszawa KLONECKI W., 1999, Statystyka dla inżynierów, Wydawnictwo Naukowe PWN, Warszawa DAVIS J.C., 1973, Statistics and data analysis In geology, John Wiley and Sons., New York,(istnieje tłumaczenie na język rosyjski, wydane przez Izd. Mir, Moskwa, 1977).
Learning outcomes:	After completion of lecture a student: • calculates statistical parameters, creates distributive series, interprets their graphically, • calculates confidence intervals for average value and variance, • verifies statistical hypothesis connected with parameters and distributions (chi-square test, Kolmogov`s test), • determines equations of regression lines and coefficients of linear correlations, • determines curvilinear regressions, • contrives to interpret results obtained by using statistical computer programs.
Assessment methods and assessment criteria:	Credit requirements: • knowledge of the materials presented on lectures, • applications of knowledge to solve practical examples. Written test with applications of received knowledge to solve practical problems (numerical examples), there is possible to use lecture notes.
Practical placement:	(in Polish) brak

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU W CW CW TH WYK FR CW
Type of class:	Classes, 30 hours, 36 places more information Lecture, 30 hours, 36 places more information
Coordinators:	Jacek Sadowski
Group instructors:	Roman Korsak, Wanda Niemyska, Jacek Sadowski
Students list:	(inaccessible to you)
Examination:	Course - Grading Classes - No assessment Lecture - Grading

Course descriptions are protected by copyright.
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